# Regress essay style on SAT score for Tables 3 and S2

library(caret)
library(tidyverse)

merged_df <- read.csv("merged_final.csv")

set.seed(1993)
merged_folds <- trainControl(method = "cv", number = 10)
merged_liwc <- as.matrix(merged_df[,76:167])

merged_df <- as.data.frame(cbind(merged_df$RSAT_TOTAL_SCORE, merged_liwc))

merged_mod <- train(V1 ~ ., method = "lm",
                    data = merged_df, trControl = merged_folds)

print(merged_mod)

################################################################################

creativ_df <- read.csv("creative_final.csv")

set.seed(1993)
creativ_folds <- trainControl(method = "cv", number = 10)
creativ_liwc <- as.matrix(creativ_df[,56:147])

creativ_df <- as.data.frame(cbind(creativ_df$RSAT_TOTAL_SCORE, creativ_liwc))

creativ_mod <- train(V1 ~ ., method = "lm",
                     data = creativ_df, trControl = creativ_folds)

print(creativ_mod)

################################################################################

signif_df <- read.csv("signif_final.csv")

set.seed(1993)
signif_folds <- trainControl(method = "cv", number = 10)
signif_liwc <- as.matrix(signif_df[,56:147])

signif_df <- as.data.frame(cbind(signif_df$RSAT_TOTAL_SCORE, signif_liwc))

signif_mod <- train(V1 ~ ., method = "lm",
                    data = signif_df, trControl = signif_folds)

print(signif_mod)
